Abstract: Trajectory anomaly detection is becoming increasingly important in various fields such as smart cities, autonomous vehicles, and video surveillance. In recent years, pattern learning-based ...

Abstract: Time series anomaly detection (TSAD) focuses on identifying whether observations in streaming data deviate significantly from normal patterns. With the prevalence of connected devices, ...

EVERGLADES, FLA. (WSVN) — A pair of python hunters stumbled across a python swim party that might offer new insights into their nesting patterns in Florida. Professional python hunters Guillermo ...

A complete end-to-end Streaming Data Analytics (SDA) project that generates real-time weather data, applies SDA filters (Moving Average, EWMA), detects anomalies using Isolation Forest, and visualizes ...

5.1 RQ1: How does our proposed anomaly detection model perform compared to the baselines? 5.2 RQ2: How much does the sequential and temporal information within log sequences affect anomaly detection?

This repository contains an end-to-end MLOps project that builds, tests, and containerizes a real-time anomaly detection API using time-series data. The Numenta Anomaly Benchmark (NAB) dataset is used ...

ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...

College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang, China The final, formatted version of the article will be published soon. This study proposes a ...

Intrusion detection systems (IDS) and anomaly detection techniques are critical components of modern cybersecurity, enabling the identification of malicious activities and system irregularities in ...